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Scientists increasingly rely on Python tools to perform scalable distributed memory array operations using rich, NumPy-like expressions. However, many of these tools rely on dynamic schedulers optimized for abstract task graphs, which often…
Electronic logbooks contain valuable information about activities and events concerning their associated particle accelerator facilities. However, the highly technical nature of logbook entries can hinder their usability and automation. As…
An essential part of building a data-driven organization is the ability to handle and process continuous streams of data to discover actionable insights. The explosive growth of interconnected devices and the social Web has led to a large…
Traditional database systems are built around the query-at-a-time model. This approach tries to optimize performance in a best-effort way. Unfortunately, best effort is not good enough for many modern applications. These applications…
The reliability of cloud platforms is of significant relevance because society increasingly relies on complex software systems running on the cloud. To improve it, cloud providers are automating various maintenance tasks, with failure…
Recent advances in query optimization have shifted from traditional rule-based and cost-based techniques towards machine learning-driven approaches. Among these, reinforcement learning (RL) has attracted significant attention due to its…
Cloud-native applications are intentionally designed for the cloud in order to leverage cloud platform features like horizontal scaling and elasticity - benefits coming along with cloud platforms. In addition to classical (and very often…
During the last few years, the explosion of Big Data has prompted cloud infrastructures to provide cloud-based database services as cost effective, efficient and scalable solutions to store and process large volume of data. Hence, NoSQL…
Automated logging statement generation supports developers in documenting critical software runtime behavior. Given the great success in natural language generation and programming language comprehension, large language models (LLMs) might…
Read-optimized columnar databases use differential updates to handle writes by maintaining a separate write-optimized delta partition which is periodically merged with the read-optimized and compressed main partition. This merge process…
We have created a cloud-based service that allows the end users to run tests on multiple different databases to find which databases are most suitable for their project. From our research, we could not find another application that enables…
Spark is an in-memory analytics platform that targets commodity server environments today. It relies on the Hadoop Distributed File System (HDFS) to persist intermediate checkpoint states and final processing results. In Spark, immutable…
Cloud computing systems promise to offer subscription-oriented, enterprise-quality computing services to users worldwide. With the increased demand for delivering services to a large number of users, they need to offer differentiated…
Linearizable datastores are desirable because they provide users with the illusion that the datastore is run on a single machine that performs client operations one at a time. To reduce the performance cost of providing this illusion, many…
IT environments typically have logging mechanisms to monitor system health and detect issues. However, the huge volume of generated logs makes manual inspection impractical, highlighting the importance of automated log analysis in IT…
The explosive increase in data demand coupled with the rapid deployment of various wireless access technologies have led to the increase of number of multi-homed or multi-interface enabled devices. Fully exploiting these interfaces has…
Extracting insights from Electronic Health Record (EHR) databases often requires SQL expertise, creating a barrier for clinical decision-making and research. A promising approach is to use Large Language Models (LLMs) to translate natural…
Object-based parallel file systems have emerged as promising storage solutions for high-performance computing (HPC) systems. Despite the fact that object storage provides a flexible interface, scheduling highly concurrent I/O requests that…
Robots have inherently limited onboard processing, storage, and power capabilities. Cloud computing resources have the potential to provide significant advantages for robots in many applications. However, to make use of these resources,…
Basic Linear Algebra Subprograms (BLAS) is a core library in scientific computing and machine learning. This paper presents FT-BLAS, a new implementation of BLAS routines that not only tolerates soft errors on the fly, but also provides…